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Analysis of predictive maintenance using thermography technique on feeder 5006 (#1757)

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Date of Conference

July 15-17, 2026

Published In

"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"

Location of Conference

Santiago (Chile)

Authors

Callacondo Acero, Cristian Ronald

Chura Acero, Julio Fredy

Chayña Velasquez, Omar

Paredes Pareja, Walter Oswaldo

Quiñonez Choquecota, Jose

Wilson Percy Clavetea Meneses, Wilson Percy

Gutierrez Gallegos, Adhemir Homero

Abstract

The objective of this study was to examine the operational condition of Feeder 5006 at the Juliaca Electrical Substation through the application of infrared thermography as a predictive maintenance tool, with the aim of identifying hot spots in its components and reducing the risk of unplanned failures. The main problem addressed was the lack of a systematic thermal diagnosis that would allow the timely detection of thermal anomalies associated with overloads, defective connections, and equipment deterioration, which affect the reliability and continuity of service. The methodology employed was based on field thermographic inspection, under previously established technical parameters and applying the NETA standard for the classification of thermal faults. Fifty-one medium-voltage structures of the feeder were evaluated, recording ambient, maximum, and reference temperatures, from which the thermal delta and the priority level of each detected anomaly were determined. The results revealed the presence of thermal faults of varying severity, with severe and moderate conditions predominating, as well as the identification of critical points with temperature differences exceeding forty degrees Celsius, which require immediate intervention. Finally, it was demonstrated that infrared thermography is an effective tool for predictive maintenance, as it enables the early identification of anomalous conditions that cannot be detected through conventional visual inspections, contributing to timely technical decision-making and the prioritization of corrective actions. Likewise, it strengthens the operational reliability of the feeder and optimizes institutional maintenance resources.

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